基于梯度方向二值模式特征的飞机翼尖跟踪技术

Aircraft Wingtip Tracking Algorithm Based on Oriented Gradient Local Binary Pattern

研究基于视频图像分析与定位的飞机翼尖跟踪技术,为飞机地面移动提供安全保障。现有图像特征进行翼尖跟踪经常失效且计算效率低下,本文结合纹理和轮廓信息,提出以梯度方向二值模式(OG_LBP)为特征的粒子滤波跟踪算法,降低特征维数的同时建立局部和全局的翼尖特征直方图描述,提高识别效果。同时,该算法在粒子滤波基本框架之下,结合当前观测信息,通过粒子传播半径的自适应更新建立系统状态模型,降低粒子集的衰减程度,提高算法效率。实验结果表明,该算法有效降低计算复杂度,在各种复杂背景下均可实现各种翼尖实时、有效的跟踪,并更具鲁棒性。

In order to provide security assurance for aircraft ground movement,wingtip tracking is proposed which is based on video image processing and analysis techniques.Due to the poor performance of the existing tracking features for a wingtip,this paper presents a new tracking algorithm within a particle filtering tracking framework which adopts oriented gradient local binary pattern（OG_LBP） descriptors to integrate texture and contour information.The OG_LBP descriptor not only reduces the histogram dimensionality but also expresses both local and holistic features of the wingtip image to enhance the discrimination.In addition,via combining the observation information of the current frame,the new tracking algorithm establishes a model of the target state.Furthermore,the radius of particle propagation is updated adaptively by the similarity between the target model and each hypothesis of the particle,which can overcome the degeneracy problem in particle filtering and result in low computational cost.Experimental results show that the proposed algorithm can achieve an accurate and robust tracking performance for different wingtips with complex background in real-time.